The process of object recognition is one of the most widely used video-analysis and image-analysis techniques employed today. In the public-safety context, a vast amount of visual data is obtained on a regular, indeed often substantially continuous basis, from a plurality of sources. Oftentimes one would wish to identify, e.g., a person of interest in these images and recordings. It could be the case that the quick and accurate identification of said person of interest is of paramount importance to the safety of the public, whether in an airport, a train station, a high-traffic outdoor space, or some other location. Among other benefits, object recognition can enable public-safety responders to identify objects of interest promptly and correctly. It is often the case, however, that the quantity of the video frames being input to—and analyzed by—object-recognition software is correlated with the ability to rapidly view and quickly interpret the results. Lengthy videos cannot be studied in their entirety due to time constraints and even a time-lapse representation still suffers from a persistent problem (i.e., the video is not relevant when the object of interest is absent).
To reduce the negative impact of excess video, various object of interest extraction tools can be used. One limited category of such tools relies on fixed camera position and orientation. Accordingly, for this reason and others, there is a need for methods and systems for object recognition and link integration in a composite video stream.
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The apparatus and method components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.